class_docstr: BERT encoder for pre-tokenized text.
class_docstr_tok: ["BERT","encoder","for","pre-tokenized","text","."]
code: def max_minibatch_size(self):
      # Rough heuristic for how much we can handle on one GPU with 12G of memory.
      return 64 if self.model.config.num_hidden_layers <= 12 else 32
  
file_path: lit/lit_nlp/examples/coref/encoders.py
imports: import os
  from lit_nlp.api import model
  from lit_nlp.api import types
  from lit_nlp.examples.coref import retokenize
  from lit_nlp.examples.models import model_utils
  from lit_nlp.lib import utils
  import numpy
  import tensorflow
  import transformers
label_desc: Use image node_id 5 for calling the BertEncoderWithOffsets obj's underlying member method code with example usage: obj.max_minibatch_size() and returns: unknown